Consensus Recommendations for the Diagnosis and Management of Well-Differentiated Gastroenterohepatic Neuroendocrine Tumours: A Revised Statement from a Canadian National Expert Group
Bibliographic record
Abstract
Well-differentiated neuroendocrine tumours (nets-previously called "carcinoid tumours") are relatively rare tumours originating from the diffuse neuroendocrine system; they are found most often in the bronchial or gastrointestinal systems. In Canada, gastroenterohepatic NETS represent less than 0.25% of oncology cases. Because of the relative rarity of these tumours, diagnostic and therapeutic approaches vary and are often based on individual physician experience. A number of European and North American groups have developed consensus guidelines for the diagnosis and management of well-differentiated gastroenterohepatic NETS, and in 2006, Canadian consensus guidelines were published by a Canadian expert group. The updated and expanded current Canadian guidelines are based on a consensus meeting held in Paris, France, in 2008 and are based on the most current literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".